Oral administration of LPS and lipoteichoic acid prepartum modulated reactants of innate and humoral immunity in periparturient dairy cows
Bibliographic record
Abstract
The study evaluated the effects of repeated oral exposure to LPS and lipoteichoic acid (LTA) on immune responses of dairy cows. Thirty pregnant Holstein cows were randomly assigned to two treatment groups. Cows received orally either 2 ml of 0.85% sterile saline solution (control group), or 2 ml of sterile saline solution containing three doses of LPS from Escherichia coli 0111 : B4 along with a flat dose of LTA from Bacillus subtilis. Blood and saliva samples were collected and analyzed for serum amyloid A (SAA); LPS-binding protein (LBP); anti-LPS plasma IgA, IgG and IgM; TNF-α; and IL-1. Results showed greater concentrations of IgA in the saliva of treated cows compared with the controls (P < 0.01). Treated cows had lower plasma concentrations of anti-LPS IgA, IgG and IgM Abs, and TNF-α than the controls (P < 0.05). There was a tendency for the concentrations of plasma LBP (P = 0.06) and haptoglobin (P = 0.10) to be lesser in the treatment group, although no differences were found in the concentration of plasma SAA and IL-1 (P > 0.10). Overall, the results of this study indicate that repeated oral administration with LPS and LTA stimulates innate and humoral immune responses in periparturient dairy cows.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".